1. Field of the Invention
The present invention relates generally to a system and method for managing a semiconductor manufacturing process and, more particularly, to a system and method for managing yield in a semiconductor fabrication process.
2. Description of the Prior Art
The semiconductor manufacturing industry is continually evolving its fabrication processes and developing new processes to produce smaller and smaller geometries of the semiconductor devices being manufactured, because smaller devices typically generate less heat and operate at higher speeds than larger devices. Currently, a single integrated circuit chip may contain over one billion patterns. Consequently, semiconductor fabrication processes are extremely complex, and hundreds of processing steps may be involved. The occurrence of a mistake or small error at any of the process steps or tool specifications may cause lower yield in the final semiconductor product, where yield may be defined as the number of functional devices produced by the process as compared to the theoretical number of devices that could be produced assuming no bad devices.
Improving yield is a critical problem in the semiconductor manufacturing industry and has a direct economic impact on it. In particular, a higher yield translates into more devices that may be sold by the manufacturer, and, hence, greater profits.
Typically, semiconductor manufacturers collect data about various semiconductor fabrication process parameters and analyze the data and, based on data analysis, adjust process steps or tool specifications in an attempt to improve the yield of the process. Today, the explosive growth of database technology has facilitated the yield analyses that each manufacturer performs. In particular, the database technology has far outpaced the yield management analysis capability when using conventional statistical techniques to interpret and relate yield to major yield factors. This has created a need for a new generation of tools and techniques for automated and intelligent database analysis for semiconductor yield management.
Many conventional yield management systems have a number of limitations and disadvantages which make them undesirable to the semiconductor manufacturing industry. For example, conventional systems may require some manual processing which slows the analysis and makes the system susceptible to human error. In addition, these conventional systems may not handle both continuous (e.g., temperature) and categorical (e.g., Lot 1, Lot 2, etc.) yield management variables. Some conventional systems cannot handle missing data elements and do not permit rapid searching through hundreds of yield parameters to identify key yield factors. Some conventional systems output data that is difficult to understand or interpret even by knowledgeable semiconductor yield management personnel. In addition, conventional systems typically process each yield parameter separately, which is time consuming and cumbersome and cannot identify more than one parameter at a time.
U.S. Pat. No. 6,470,229 B1 assigned to the same assignee as the present application discloses a yield management system and technique for processing a yield data set containing one or more prediction variable values and one or more response variable values to remove prediction variables with missing values and data sets with missing values. The processed data can then be used to generate a yield model preferably in the form of a decision tree. The system can also accept user input to modify the generated model.
While the yield management system and technique disclosed in aforementioned U.S. Pat. No. 6,470,229 B1 provide a powerful yield management tool, one limitation is that the criteria employed for processing data sets may remove data sets with missing values, even though the data sets may contain usable data respecting a significant prediction variable that may be useful in generating the model. Also, while the disclosed system and technique provide fundamental splitting rules for generating a decision-tree based model, there are instances in which the system is limited in the variety of splitting rules and also limited in accommodating modification of the model based on the knowledge of the user.
Thus, it would be desirable to provide a yield management system and method which overcome the above limitations and disadvantages of conventional systems and facilitate building a more accurate model. It is to this end that the present invention is directed. The various embodiments of the present invention provide many advantages over conventional methods and yield management systems.